Register Now: Beyond EDC: Designing a Connected Data Strategy for Predictive Clinical Development
Commentary|Videos|September 30, 2025

2025 SCRS Global Site Solutions Summit: How Sites Can Overcome Technology Burdens in Clinical Trials

Steve Rosenberg, CEO, uMotif, discusses the challenges sites face with eCOA, eConsent, and ePRO platforms and the support needed to reduce technical burdens.

In a video interview with Applied Clinical Trials ahead of the 2025 SCRS Global Site Solutions Summit, Steve Rosenberg, CEO, uMotif, discussed the challenges sites face in implementing eClinical technologies like eCOA, eConsent, and ePRO. He highlighted the burden on sites, which are not equipped to handle tech support, and emphasized the need for multilingual support and direct patient-site relationships. Vendors are aiming to simplify site management by providing a single sign-on for various systems and dashboards. Rosenberg also advocated for sponsors to invest in site technology to reduce administrative overhead. He concluded by exploring the importance of integrating technology training with protocol training to streamline study startup and reduce training time.

ACT: What are the biggest pain points sites are facing when implementing and using eCOA, eConsent, or ePRO platforms, and how can technology providers better address those burdens?

Rosenberg: I love that question. If you think about what a site is in clinical research, they're research people. They like science. They sign up because they'd like the molecule, and they want to be on the forefront of the research and the new breakthroughs that are coming for disease. What they're not are tech support systems.

Over the years, as more technology has been put in the hands of the patients, it's done through the site. The sites are being asked to set up Bluetooth, provision phones, set up wearable devices, and all kinds of things. It puts a big burden on the site. This technology is awesome, it makes clinical trials so much better, but it puts a burden on sites. The sites are also the place that the patients go to with their questions. Now, what vendors can do, and what we do, is we set up multilingual supports where patients and sites can call for help, but I really think what's going to need to happen is the sites are going to have to decide that they're going to have to provide that kind of support directly to the patients, to foster that relationship between the patient and the site, and not push it off to anyone else. As a vendor, we do what we can to help and support, but the sites are really not set up to do that yet.


Related to this article

© photon_photo - © photon_photo - stock.adobe.com
Standardized measurement across five oncology centers found that clinical research coordinators rated eSource-enabled workflows positively (Overall Mean Satisfaction 5.79 of 7), with reduced manual entry and electronic data transfer earning strong marks, while perceived reduction in sponsor and monitor queries lagged as the one domain below threshold.
Where the Industry Is Headed as Clinical, Operational, and Real-World Data Connect
In this video interview, Rajneesh Patil, global head of AI, digital, and innovation in clinical development at Syneos Health, describes the industry’s trajectory toward a unified intelligence orchestration environment—and explains why the future isn’t one model that knows everything, but a trusted system that brings the right evidence to the right human decision.
What Expanding AI Ecosystems Mean for Sponsor Complexity and Oversight
In this video interview, Rajneesh Patil, global head of AI, digital, and innovation in clinical development at Syneos Health, argues that CROs must act as orchestrators rather than aggregators—and that the real test of any AI ecosystem is whether it reduces sponsor coordination burden or just hands it back to them.
Where AI Governance in Clinical Development Falls Short
In this video interview, Rajneesh Patil, global head of AI, digital, and innovation in clinical development at Syneos Health, identifies three recurring failure modes in AI governance frameworks—and explains why responsible AI must be an ongoing operating discipline, not a one-time approval gate.